Recommender Systems: An Applied Approach using Deep Learning - Candidate Tower and Retrieval System

The video tutorial covers the development of a candidate tower using TF Keras, focusing on embedding layers and vocabulary setup. It then explains the creation of a retrieval system to evaluate model accuracy using positive user-item pairs. The tutorial demonstrates implementing a retrieval task with Tensorflow's factorized top K metric, using a beer list as candidates. Finally, it summarizes the retrieval model and hints at the next component, the loss function, to be discussed in the following video.

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